Abstract

In this study, we introduce a novel maze task designed to investigate naturalistic motor learning in bimanual coordination. We developed and validated an extended set of movement primitives tailored to capture the full spectrum of scenarios encountered in a maze game. Over a 3-day training period, we evaluated participants’ performance using these primitives and a custom-developed software, enabling precise quantification of performance. Our methodology integrated the primitives with in-depth kinematic analyses and thorough thumb pressure assessments, charting the trajectory of participants’ progression from novice to proficient stages. Results demonstrated consistent improvement in maze performance and significant adaptive changes in joint behaviors and strategic recalibrations in thumb pressure distribution. These findings highlight the central nervous system’s adaptability in orchestrating sophisticated motor strategies and the crucial role of tactile feedback in precision tasks. The maze platform and setup emerge as a valuable foundation for future experiments, providing a tool for the exploration of motor learning and coordination dynamics. This research underscores the complexity of bimanual motor learning in naturalistic environments, enhancing our understanding of skill acquisition and task efficiency while emphasizing the necessity for further exploration and deeper investigation into these adaptive mechanisms.

Details

Title
Exploring motor skill acquisition in bimanual coordination: insights from navigating a novel maze task
Author
Cienfuegos, Miguel 1 ; Maycock, Jonathan 2 ; Naceri, Abdeldjallil 3 ; Düsterhus, Tobias 4 ; Kõiva, Risto 4 ; Schack, Thomas 1 ; Ritter, Helge 4 

 Bielefeld University, Neurocognition and Action - Biomechanics Group, Bielefeld, Germany (GRID:grid.7491.b) (ISNI:0000 0001 0944 9128) 
 Margin UG, Bielefeld, Germany (GRID:grid.7491.b) 
 Technical University of Munich, Munich Institute of Robotics and Machine Intelligence (MIRMI), Munich, Germany (GRID:grid.6936.a) (ISNI:0000 0001 2322 2966) 
 Bielefeld University, Neuroinformatics Group, Bielefeld, Germany (GRID:grid.7491.b) (ISNI:0000 0001 0944 9128) 
Pages
18887
Publication year
2024
Publication date
2024
Publisher
Nature Publishing Group
e-ISSN
20452322
Source type
Scholarly Journal
Language of publication
English
ProQuest document ID
3092981345
Copyright
© The Author(s) 2024. This work is published under http://creativecommons.org/licenses/by/4.0/ (the “License”). Notwithstanding the ProQuest Terms and Conditions, you may use this content in accordance with the terms of the License.